Abstract: Hazard-resultant effects to land and buildings are predicted based on various inputs. Hazards may include any appropriate type of hazard (e.g., flood, wildfire, climate-related hazards, or the like). Inputs may include the likelihood that that a specific type of hazard may occur for various scenarios, terrestrial boundaries, property boundaries, census geographies, or the like. Relationships between the inputs are determined and used to quantify parameters pertaining to a specific type of hazard. For example, the depth of flood water may be predicted for a particular terrestrial boundary, a city or town, or a building, for specific climate scenarios. A risk likelihood of the quantified parameter may be determined for a particular period of time and environment. For example, flooding to a building may be determined, broken down by depth threshold and year of annual risk for specific climate scenarios. Economic loss also may be predicted.

Abstract: Hazard-resultant effects to land and buildings are predicted based on various inputs. Hazards may include any appropriate type of hazard (e.g., flood, wildfire, climate-related hazards, or the like). Inputs may include the likelihood that that a specific type of hazard may occur for various scenarios, terrestrial boundaries, property boundaries, census geographies, or the like. Relationships between the inputs are determined and used to quantify parameters pertaining to a specific type of hazard. For example, the depth of flood water may be predicted for a particular terrestrial boundary, a city or town, or a building, for specific climate scenarios. A risk likelihood of the quantified parameter may be determined for a particular period of time and environment. For example, flooding to a building may be determined, broken down by depth threshold and year of annual risk for specific climate scenarios. Economic loss also may be predicted.

Abstract: Hazard-resultant effects to land and buildings are predicted based on various inputs. Hazards may include any appropriate type of hazard (e.g., flood, wildfire, climate-related hazards, or the like). Inputs may include the likelihood that that a specific type of hazard may occur for various scenarios, terrestrial boundaries, property boundaries, census geographies, or the like. Relationships between the inputs are determined and used to quantify parameters pertaining to a specific type of hazard. For example, the depth of flood water may be predicted for a particular terrestrial boundary, a city or town, or a building, for specific climate scenarios. A risk likelihood of the quantified parameter may be determined for a particular period of time and environment. For example, flooding to a building may be determined, broken down by depth threshold and year of annual risk for specific climate scenarios. Economic loss also may be predicted.

Abstract: Examples related to facilitating the training, assessment, and dispatching of technicians to a customer location for at least the purpose of servicing or repairing machines, devices, or systems present at the customer location are presented. The technician can be selected for dispatch to the customer location by review of database information, including training information for the technician, among other things. While at the customer location, the technician can be provided with training information delivered via a training module, where such training material content can comprise written materials, photos, video, virtual assistance, remote assistance, games, or the like. The technician can generate videos or other collateral while at the customer location, which can be included for use in a library of training materials for subsequent use, or for other purposes.

Abstract: Hazard-resultant effects to land and buildings are predicted based on various inputs. Hazards may include any appropriate type of hazard (e.g., flood, wildfire, climate-related hazards, or the like). Inputs may include the likelihood that that a specific type of hazard may occur for various scenarios, terrestrial boundaries, property boundaries, census geographies, or the like. Relationships between the inputs are determined and used to quantify parameters pertaining to a specific type of hazard. For example, the depth of flood water may be predicted for a particular terrestrial boundary, a city or town, or a building, for specific climate scenarios. A risk likelihood of the quantified parameter may be determined for a particular period of time and environment. For example, flooding to a building may be determined, broken down by depth threshold and year of annual risk for specific climate scenarios. Economic loss also may be predicted.

Abstract: Examples related to facilitating the training, assessment, and dispatching of technicians to a customer location for at least the purpose of servicing or repairing machines, devices, or systems present at the customer location are presented. The technician can be selected for dispatch to the customer location by review of database information, including training information for the technician, among other things. While at the customer location, the technician can be provided with training information delivered via a training module, where such training material content can comprise written materials, photos, video, virtual assistance, remote assistance, games, or the like. The technician can generate videos or other collateral while at the customer location, which can be included for use in a library of training materials for subsequent use, or for other purposes.